{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "ModelC.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oqAZmW7JXZ8P",
        "colab_type": "text"
      },
      "source": [
        "# Clone code and download weights"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lAhH90gNTKho",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 134
        },
        "outputId": "314941a4-1e5e-4917-ca30-603204396cf7"
      },
      "source": [
        "# clone model\n",
        "!git clone https://github.com/richarduuz/Research_Project"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'Research_Project'...\n",
            "remote: Enumerating objects: 331, done.\u001b[K\n",
            "remote: Counting objects: 100% (331/331), done.\u001b[K\n",
            "remote: Compressing objects: 100% (226/226), done.\u001b[K\n",
            "remote: Total 331 (delta 97), reused 264 (delta 56), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (331/331), 14.55 MiB | 19.81 MiB/s, done.\n",
            "Resolving deltas: 100% (97/97), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dnxf34beVy9F",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 185
        },
        "outputId": "fb514cdb-6da7-4815-dc94-0552f528c176"
      },
      "source": [
        "# download weights\n",
        "%cd /content/Research_Project/ModelC/face_modules/\n",
        "!gdown https://drive.google.com/uc?id=15nZSJ2bAT3m-iCBqP3N_9gld5_EGv4kp\n",
        "%cd /content/Research_Project/ModelC/saved_models/\n",
        "!gdown https://drive.google.com/uc?id=1iANX7oJoXCEECNzBEW1xOpac2tDOKeu9"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/Research_Project/ModelC/face_modules\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=15nZSJ2bAT3m-iCBqP3N_9gld5_EGv4kp\n",
            "To: /content/Research_Project/ModelC/face_modules/model_ir_se50.pth\n",
            "175MB [00:12, 14.1MB/s]\n",
            "/content/Research_Project/ModelC/saved_models\n",
            "Downloading...\n",
            "From: https://drive.google.com/uc?id=1iANX7oJoXCEECNzBEW1xOpac2tDOKeu9\n",
            "To: /content/Research_Project/ModelC/saved_models/G_latest.pth\n",
            "737MB [00:07, 98.9MB/s]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4-sG1Hd2XozG",
        "colab_type": "text"
      },
      "source": [
        "# Load Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8x0F0vw1YSFv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "b7dda6a5-e995-4dc7-e66f-03d315cfa118"
      },
      "source": [
        "%cd /content/Research_Project/ModelC/"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/Research_Project/ModelC\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dGUfLUjNXoKo",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import sys\n",
        "import torch\n",
        "sys.path.append('./face_modules/')\n",
        "import torchvision.transforms as transforms\n",
        "import torch.nn.functional as F\n",
        "from face_modules.model import Backbone, Arcface, MobileFaceNet, Am_softmax, l2_norm\n",
        "from network.AEI_Net import *\n",
        "from face_modules.mtcnn import *\n",
        "import cv2\n",
        "import PIL.Image as Image\n",
        "import numpy as np\n",
        "import configparser"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X0fe6jkSYe4u",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "detector = MTCNN()\n",
        "device = torch.device('cuda')\n",
        "G = AEI_Net(c_id=512)\n",
        "G.eval()\n",
        "G.load_state_dict(torch.load('./saved_models/G_latest.pth', map_location=torch.device('cpu')))\n",
        "G = G.cuda()\n",
        "\n",
        "arcface = Backbone(50, 0.6, 'ir_se').to(device)\n",
        "arcface.eval()\n",
        "arcface.load_state_dict(torch.load('./face_modules/model_ir_se50.pth', map_location=device), strict=False)\n",
        "\n",
        "test_transform = transforms.Compose([\n",
        "    transforms.ToTensor(),\n",
        "    transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))\n",
        "])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CupgiblbU6KR",
        "colab_type": "text"
      },
      "source": [
        "# Image Inference"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "aArVcgj8USzd",
        "colab_type": "text"
      },
      "source": [
        "## Upload source image"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qK6ERNWTUOZJ",
        "colab_type": "code",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 94
        },
        "outputId": "e687b0cb-9626-403b-8037-e3c190563d28"
      },
      "source": [
        "from google.colab import files\n",
        "source_img = files.upload()\n",
        "source_img_name = list(source_img.keys())[0]\n"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-cc8970c2-29b5-411c-8a1d-db23a9fbb7e1\" name=\"files[]\" multiple disabled />\n",
              "     <output id=\"result-cc8970c2-29b5-411c-8a1d-db23a9fbb7e1\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving 00000000.jpg to 00000000 (2).jpg\n",
            "00000000.jpg\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HntTfyGCUyS-",
        "colab_type": "text"
      },
      "source": [
        "## Upload target image"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K6TLv226U28G",
        "colab_type": "code",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 77
        },
        "outputId": "580e58f7-d52d-4cfa-931f-1265fd8cead6"
      },
      "source": [
        "from google.colab import files\n",
        "target_img = files.upload()\n",
        "target_img_name = list(target_img.keys())[0]"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-72c47976-76d4-4aba-aa59-17d93b022e56\" name=\"files[]\" multiple disabled />\n",
              "     <output id=\"result-72c47976-76d4-4aba-aa59-17d93b022e56\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving 00000001.jpg to 00000001.jpg\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EMYJ0HM5VcM9",
        "colab_type": "text"
      },
      "source": [
        "## Inference"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AOBmjCupVfAn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 340
        },
        "outputId": "f71db449-b40e-416c-df0c-52e1bbdf1661"
      },
      "source": [
        "from google.colab.patches import cv2_imshow\n",
        "Xs_raw = cv2.imread(source_img_name)\n",
        "try:\n",
        "    Xs = detector.align(Image.fromarray(Xs_raw[:, :, ::-1]), crop_size=(256, 256))\n",
        "except Exception as e:\n",
        "    print('the source image is wrong, please change the image')\n",
        "Xs_raw = np.array(Xs)[:, :, ::-1]\n",
        "Xs = test_transform(Xs)\n",
        "Xs = Xs.unsqueeze(0).cuda()\n",
        "\n",
        "with torch.no_grad():\n",
        "    embeds = arcface(F.interpolate(Xs[:, :, 19:237, 19:237], (112, 112), mode='bilinear', align_corners=True))\n",
        "\n",
        "Xt_raw = cv2.imread(target_img_name)\n",
        "try:\n",
        "    Xt, trans_inv = detector.align(Image.fromarray(Xt_raw[:, :, ::-1]), crop_size=(256, 256), return_trans_inv=True)\n",
        "except Exception as e:\n",
        "    print('the target image is wrong, please change the image')\n",
        "Xt_raw = Xt_raw.astype(np.float)/255.0\n",
        "Xt = test_transform(Xt)\n",
        "Xt = Xt.unsqueeze(0).cuda()\n",
        "\n",
        "mask = np.zeros([256, 256], dtype=np.float)\n",
        "for i in range(256):\n",
        "    for j in range(256):\n",
        "        dist = np.sqrt((i-128)**2 + (j-128)**2)/128\n",
        "        dist = np.minimum(dist, 1)\n",
        "        mask[i, j] = 1-dist\n",
        "mask = cv2.dilate(mask, None, iterations=20)\n",
        "\n",
        "with torch.no_grad():\n",
        "    Yt, _ = G(Xt, embeds)\n",
        "    Yt = Yt.squeeze().detach().cpu().numpy().transpose([1, 2, 0])*0.5 + 0.5\n",
        "    Yt = Yt[:, :, ::-1]\n",
        "    Yt_trans_inv = cv2.warpAffine(Yt, trans_inv, (np.size(Xt_raw, 1), np.size(Xt_raw, 0)), borderValue=(0, 0, 0))\n",
        "    mask_ = cv2.warpAffine(mask,trans_inv, (np.size(Xt_raw, 1), np.size(Xt_raw, 0)), borderValue=(0, 0, 0))\n",
        "    mask_ = np.expand_dims(mask_, 2)\n",
        "    Yt_trans_inv = mask_*Yt_trans_inv + (1-mask_)*Xt_raw\n",
        "    cv2_imshow(Yt_trans_inv*255)\n",
        "    cv2.imwrite('./result.jpg',Yt_trans_inv*255)\n",
        "    print(\"the result image has been saved\")\n"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "./face_modules/mtcnn_pytorch/src/matlab_cp2tform.py:90: FutureWarning: `rcond` parameter will change to the default of machine precision times ``max(M, N)`` where M and N are the input matrix dimensions.\n",
            "To use the future default and silence this warning we advise to pass `rcond=None`, to keep using the old, explicitly pass `rcond=-1`.\n",
            "  r, _, _, _ = lstsq(X, U)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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dt9eP7394+fTh1//u3w9jKgBbac/CRU5j/8lZ+Hujwt8Ag76pkgVBitWvJVfx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\nfSe0MSzncDx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            "text/plain": [
              "<PIL.Image.Image image mode=RGB size=256x256 at 0x7F1C00A130F0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "the result image has been saved\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}